Depth can be accurately predicted from stereo matching, which can be broadly divided into binocular stereo and multi-view stereo (MVS). The former requires calibrated setups of rectified stereo pairs, and many traditional [1]}, [2]}, [3]}, [4]} and deep learning based methods [5]}, [6]}, [7]}, [8]}, [9]}, [10]}, [11]}, [12]}, [13]} have been proposed. Compared with binocular stereo, MVS methods estimate depth from a set of monocular images or a video, where the camera moves and the scene is assumed static. In this section, we briefly review deep learning based MVS methods.
